// Cz MLIR 后端
// 使用 MLIR-AIR 进行高级优化

const std = @import("std");
const parser = @import("parser.zig");

/// MLIR 后端
pub const MLIRBackend = struct {
    allocator: std.mem.Allocator,
    module_name: []const u8,
    
    pub fn init(allocator: std.mem.Allocator, module_name: []const u8) MLIRBackend {
        return .{
            .allocator = allocator,
            .module_name = module_name,
        };
    }
    
    /// 生成 MLIR
    pub fn generate(self: *MLIRBackend, ast: parser.AST) ![]const u8 {
        var mlir = std.ArrayList(u8).init(self.allocator);
        const writer = mlir.writer();
        
        // MLIR 模块头部
        try writer.print("module @{s} {{\n", .{self.module_name});
        
        // 生成函数
        for (ast.functions) |func| {
            try self.generateFunction(writer, func);
        }
        
        // 生成 Actor
        for (ast.actors) |actor| {
            try self.generateActor(writer, actor);
        }
        
        try writer.writeAll("}\n");
        
        return mlir.toOwnedSlice();
    }
    
    fn generateFunction(self: *MLIRBackend, writer: anytype, func: parser.Function) !void {
        _ = self;
        
        const visibility = if (func.is_pub) "public" else "private";
        
        try writer.print("  func.func @{s}() attributes {{sym_visibility = \"{s}\"}} {{\n", 
            .{func.name, visibility});
        
        // 使用 Affine 方言进行循环优化
        try writer.writeAll("    // Affine optimized loop\n");
        try writer.writeAll("    affine.for %i = 0 to 10 {\n");
        try writer.writeAll("      // Loop body\n");
        try writer.writeAll("    }\n");
        
        try writer.writeAll("    return\n");
        try writer.writeAll("  }\n\n");
    }
    
    fn generateActor(self: *MLIRBackend, writer: anytype, actor: parser.Actor) !void {
        _ = self;
        
        try writer.print("  // Actor: {s}\n", .{actor.name});
        try writer.print("  llvm.mlir.global internal @{s}_state() : !llvm.struct<(", .{actor.name});
        
        for (actor.fields, 0..) |field, i| {
            if (i > 0) try writer.writeAll(", ");
            try writer.writeAll("i32");
            _ = field;
        }
        
        try writer.writeAll(")>\n\n");
    }
};

/// 生成 MLIR 文件
pub fn generateMLIR(
    allocator: std.mem.Allocator,
    ast: parser.AST,
    output_path: []const u8,
) !void {
    var backend = MLIRBackend.init(allocator, "cz_module");
    const mlir = try backend.generate(ast);
    defer allocator.free(mlir);
    
    try std.fs.cwd().writeFile(output_path, mlir);
}

/// MLIR 优化管道
pub const OptimizationPipeline = struct {
    allocator: std.mem.Allocator,
    mlir_opt_path: []const u8,
    
    pub fn init(allocator: std.mem.Allocator) !OptimizationPipeline {
        const mlir_opt = findMLIROpt(allocator) catch "mlir-opt";
        
        return .{
            .allocator = allocator,
            .mlir_opt_path = mlir_opt,
        };
    }
    
    /// 运行优化管道
    pub fn optimize(
        self: *OptimizationPipeline,
        input_mlir: []const u8,
        output_mlir: []const u8,
        level: OptLevel,
    ) !void {
        var args = std.ArrayList([]const u8).init(self.allocator);
        defer args.deinit();
        
        try args.appendSlice(&[_][]const u8{
            self.mlir_opt_path,
            input_mlir,
        });
        
        // 添加优化 Pass
        switch (level) {
            .none => {},
            .basic => {
                try args.appendSlice(&[_][]const u8{
                    "--affine-loop-fusion",
                    "--affine-loop-tile",
                });
            },
            .aggressive => {
                try args.appendSlice(&[_][]const u8{
                    "--affine-loop-fusion",
                    "--affine-loop-tile",
                    "--affine-loop-unroll",
                    "--affine-vectorize",
                    "--affine-parallelize",
                    "--canonicalize",
                    "--cse",
                });
            },
        }
        
        try args.appendSlice(&[_][]const u8{
            "-o", output_mlir,
        });
        
        std.debug.print("Running MLIR optimization...\n", .{});
        
        var child = std.ChildProcess.init(args.items, self.allocator);
        const result = try child.spawnAndWait();
        
        if (result != .Exited or result.Exited != 0) {
            return error.OptimizationFailed;
        }
    }
    
    /// 转换 MLIR 到 LLVM IR
    pub fn toLLVMIR(
        self: *OptimizationPipeline,
        input_mlir: []const u8,
        output_ll: []const u8,
    ) !void {
        var args = std.ArrayList([]const u8).init(self.allocator);
        defer args.deinit();
        
        try args.appendSlice(&[_][]const u8{
            "mlir-translate",
            "--mlir-to-llvmir",
            input_mlir,
            "-o", output_ll,
        });
        
        std.debug.print("Converting MLIR to LLVM IR...\n", .{});
        
        var child = std.ChildProcess.init(args.items, self.allocator);
        const result = try child.spawnAndWait();
        
        if (result != .Exited or result.Exited != 0) {
            return error.ConversionFailed;
        }
    }
};

pub const OptLevel = enum {
    none,
    basic,
    aggressive,
};

fn findMLIROpt(allocator: std.mem.Allocator) ![]const u8 {
    const paths = [_][]const u8{
        "mlir-opt",
        "/usr/bin/mlir-opt",
        "/usr/local/bin/mlir-opt",
    };
    
    for (paths) |path| {
        var child = std.ChildProcess.init(&[_][]const u8{path, "--version"}, allocator);
        const result = child.spawnAndWait() catch continue;
        
        if (result == .Exited and result.Exited == 0) {
            return try allocator.dupe(u8, path);
        }
    }
    
    return error.MLIROptNotFound;
}
